It is known in many applications, including self-propelled vehicle applications as seen by reference to U.S. Pat. No. 6,394,208 entitled “STARTER/ALTERNATOR CONTROL STRATEGY TO ENHANCE DRIVEABILITY OF A LOW STORAGE REQUIREMENT HYBRID ELECTRIC VEHICLE” issued to Hampo et al., to employ a dynamoelectric machine in a first mode as a motor in order to provide propulsion torque. In such applications, it is also known to reconfigure the dynamoelectric machine in a second mode as a generator, in order to capture and convert some of the potential or kinetic energy associated with the application into output electrical power, a process known as regeneration (“regenerative energy”). Moreover, in such applications, it is also known to provide an energy system, such as a battery, to power the dynamoelectric machine when operated as a motor, and to receive the regenerative energy when the dynamoelectric machine is operated as a generator. In the latter case, the regenerative energy is generally operative to increase the state of charge of the battery, until such battery is “fully” charged. Battery technologies typically used in such applications include nickel metal hydride (NiMH), lead acid (PbA) and nickel cadmium (NiCd) technologies, although energy systems employing lithium chemistry technologies, while not as prevalent as other battery technologies, are also used in practice.
The optimization of the battery is affected by the charging regimen. Presently, most optimization is done during the design phase of the battery, as opposed to “real time” optimization done while the battery is in use. Fixed charging routines based upon “expected” customer usage cycles are developed, and the battery is designed around these expected cycles. The battery is balanced to a target state-of-charge (SOC) during the design phase based upon these expected cycles of usage of the battery. That target SOC is the SOC to which the battery is balanced for the life of the battery. The life of the battery, therefore, may be considerably shortened if the target SOC based upon design projections is not optimal as compared to the “real-time” use. Other fixed charging strategies include strategies designed to achieve maximum energy storage (and output) without regard to incorporating power-based needs (such as frequent stopping and starting of a dynamoelectric machine) or the ability of the battery to absorb regenerative energy. Such fixed charging strategies are only appropriate for discharge-only products as opposed to rechargeable products.
These existing methods, while adequate, do not allow for the most useful method of optimization. Existing methods, as set forth above, neither provide for “real time” adaptation of the charging regimen to the battery while it is in use, nor do they take into account the varied applications with which a battery may be used. For example, it would generally be desirable to charge the battery to its highest possible SOC to provide the greatest range or longest duration use for the application running off the battery. However, such an approach is generally not considered optimal for more dynamic applications that involve the acceptance of regenerative energy. A lower SOC allows the battery to be at an optimal charge level to accept regenerative energy or provide dynamic power functions (repeated charging and discharging cycles).
Multiple cell lithium chemistry batteries in particular present specific challenges when developing battery charging regimens. Each cell within a multiple-cell lithium battery will have its own unique electrical characteristics, including impedance levels and SOC. If the desired battery design entails maximum energy output, one cell may need to be charged more fully than another cell within the battery. If the electrical characteristics of each cell are not tracked, the charging regimen can not result in a battery optimal for the designed use, as the regimen will be adjusted to accommodate the best performing cell. This is necessary to prevent overcharging of the cells; lithium chemistry batteries are intolerant to such overcharging. Likewise, if the battery charging design requires the battery to have capacity to accept regenerative energy, providing and accepting energy in a dynamic state as opposed to providing energy in a steady-state situation, the regimen will not provide a battery with optimal charge. The optimal SOC for each cell in those circumstances varies between cells and a “one size fits all” SOC charging strategy will not be optimum.
Therefore, there exists a need for a method that allows the cells of a battery pack to be charged to specific and individual SOC levels, unique and optimal to each individual cell, based upon data collected during the battery's operation, thereby minimizing or eliminating one or more of the above-identified problems.